Integrating text retrieval and image retrieval in XML document searching

  • Authors:

  • D. Tjondronegoro;J. Zhang;J. Gu;A. Nguyen;S. Geva

  • Affiliations:

  • Queensland University of Technology, Brisbane, Australia;Queensland University of Technology, Brisbane, Australia;Queensland University of Technology, Brisbane, Australia;Queensland University of Technology, Brisbane, Australia;Queensland University of Technology, Brisbane, Australia

  • Venue:
  • INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
  • Year:
  • 2005

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Abstract

Many XML documents contain a mixture of text and images. Images play an important role in webpage or article presentation. However, popular Information Retrieval systems still largely depend on pure text retrieval as it is believed that text descriptions including body text and the caption of images contain precise information. On the other hand, images are more attractive and easier to understand than pure text. We assume that if the image content is used in addition to the pure text-based retrieval, the retrieval result should be better than text-only or image-only retrieval. We test this hypothesis by doing a series of experiments using the Lonely Planet XML document collection. Two search engines, an XML document search engine using both content and structure based on text, and a content-based image search engine were used at the same time. The results generated by these two search engines were merged together to form a new result. This paper presents our current work, initial results and vision into future work.